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Grant Funders & Social Investors

Since the basis of our benchmarking and databases is financial data on individual organisations, we can aggregate it up into a whole series of separate, stacked, or overlapping data clusters. This allows a portfolio to be analysed from a series of perspectives and compared against a variety of sector, turnover and geographical benchmarks.

In addition to acquiring detailed profit & loss and balance sheet data, we also run a series of financial metrics calculations across the dataset. This means that we can benchmark both individual organisations and portfolio performance against the norms across a wider sector.

At the level of a programme or investment manager, this functionality allows us to answer questions such as:

  • How is my programme performing over time on a set of key metrics (turnover | contribution to reserves | revenue growth | asset growth)
  • Which organisations are performing above or below average by comparison to the rest of the portfolio?
  • Which organisations are performing above or below average by comparison to the rest of their sector | region | turnover band | asset type?
  • Which organisations are raising red flags against a set of key metrics which are bespoke to my fund or programme?
  • How are organisations performing vs. targets on a quarterly | annual basis?
  • What are my aggregated key metrics results for the portfolio this quarter | year; and what is the pattern over time?
  • How do the key metrics of this programme compare against other programmes being run in my organisation?
  • How does my cohort perform against a comparison group of organisations where we have no involvement? For example, failed applications, or a set of sector comparisons.

This functionality allows for regular reporting, management by exception, and the setting of a RAG (Red-Amber-Green) rating system on key metrics.

In addition we can aggregate up data across the whole of a funder or investor’s portfolio, and track the changes over time. This then allows us to answer questions such as:

  • What are the results on key metrics by sector?
  • How does performance vary by sector?
  • Are there variations by sector according to geography | turnover band or other profile factors?
  • Are the default rates higher in some sectors | geographies | risk profiles than others?
  • What types of selection bias are prevalent (and to what extent) by comparison to a national dataset | region | sector | IMD decile etc.?
  • What are the risk and resilience profiles of the portfolio by comparison to a national dataset?
  • How does a portfolio compare to a cohort of organisations which applied unsuccessfully to join a programme or fund?